ML

In this project, we re-implement and enhance an oper- ationalization of individual fairness that does not rely on a human specification of a distance metric. Instead, we pro- pose novel approaches to elicit and leverage side-information on equally deserving individuals to counter subordination between social groups. We model this knowledge as a fair- ness graph, and learn a unified Pairwise Fair Representation (PFR) of the data that captures both data-driven similar- ity between individuals and the pairwise side-information in fairness graph

A fun side project to predict the standings and outcome of the qualifying teams for FIFA 2022 to be held at Qatar. The dataset takes into account the last 50 years of data and ranking informations , with special focus on recent performance of the teams. Also , many teams exist whose matchup was not seen at the highest stage , so there performance with mutually opponent team was taken into consideration.

In India states earn revenue through own taxes, central taxes, non-taxes and central grants. For most states, own taxes form the largest part of the total state revenue. Taxes as per the state list includes land revenue, taxes on agricultural income, electricity duty, luxury tax, entertainment tax and stamp duty. We model this information with a regression model which achieves great accuracy for variety of state performance indicators.